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PMID: 17822390 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

"Good annotation practice" for chemical data in biology.

In silico biology ·Vol. 7 ·No. 2 Suppl ·2007-00-00 ·Pages S45-56

Degtyarenko K, Ennis M, Garavelli JS

Abstract

A structural diagram, in the form of a two-dimensional (2-D) sketch, remains the most effective portrait of a "small molecule" or chemical reaction. However, such structural diagrams, as for any other core data, cannot be used in speech (and should not be used in free text). "Good annotation practice" for biological databases is to use either consistent and widely recognised terminology or unique identifiers from a dedicated database to refer to the molecule of interest. Ideally, scientists should use terminology that is both pronounceable and meaningful. Thus, a viable solution for a bioinformatician is to use a definitive controlled vocabulary of biochemical compounds and reactions, which contains both systematic and common names. In addition, chemical ontologies provide a means for placing entities of interest into wider chemical, biological or medical contexts. We present some challenges and achievements in the standardisation of chemical language in biological databases, with emphasis on three aspects of annotation: 1. good drawing practice: how to draw unambiguous 2-D diagrams; 2. good naming practice: how to give most appropriate names; and 3. good ontology practice: how to link the entity of interest by defined logical relationships to other entities.

MeSH Terms
Computational Biology/methods Databases, Factual/standards Models, Chemical Models, Molecular Molecular Conformation Terminology as Topic Vocabulary, Controlled
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Degtyarenko Kirill
European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom. [email protected]
Ennis Marcus
Garavelli John S
Article Info
Journal
In silico biology
Abbr.
In Silico Biol
ISSN
1386-6338
Published
2007-00-00
Pages
S45-56
Language
English
Region
Netherlands
NLM ID
9815902
Subset
IM
External Links
PubMed source
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